Photometry of Type II Supernova SN 2023ixf with a Worldwide Citizen Science Network

We present highly sampled photometry of the supernova (SN) 2023ixf, a Type II SN in M101, beginning 2 days before its first known detection. To gather these data, we enlisted the global Unistellar Network of citizen scientists. These 252 observations from 115 telescopes show the SN's rising brightness associated with shock emergence followed by gradual decay. We measure a peak $M_{V}$ = -18.18 $\pm$ 0.09 mag at 2023-05-25 21:37 UTC in agreement with previously published analyses.


INTRODUCTION
Type II supernovae (SNe) are hydrogen-rich, core-collapse SNe (see Filippenko 1997 for a review of SN classification) and are among the most commonly observed SNe (e.g., Li et al. 2011). Despite their prevalence, early-time observations of these SNe are rarely available owing to the cadence of large surveys and other factors. Nevertheless, data within days after shock breakout, in which the shock wave from the collapsing core reaches the stellar photosphere, are imperative for gaining an understanding of the progenitor and explosion physics (Waxman & Katz 2017). Itagaki (2023) reported discovery of a SN in M101 (redshift z = 0.0008) in observations from 2023-05-19 17:27 (UTC dates are used throughout this paper). This SN, designated 2023ixf, offered an opportunity for amateur and professional astronomers to collect data promptly. The earliest known detection was found during spontaneous observations by Mao et al. (2023) at 2023-05-18 20:29. See Hosseinzadeh et al. (2023 and references therein for a review of early-time photometry. Perley et al. (2023) revealed SN 2023ixf as a Type II SN. The progenitor candidate has been identified in archival Spitzer Space Telescope and Hubble Space Telescope images (Szalai & Dyk 2023;Soraisam et al. 2023;Pledger & Shara 2023) as a luminous red supergiant with a dense shell of circumstellar material and long-period variability in near-to-arXiv:2307.14347v1 [astro-ph.HE] 7 Jul 2023 mid-infrared wavelengths (Jacobson-Galan et al. 2023;Jencson et al. 2023;Kilpatrick et al. 2023). Future studies will further constrain the progenitor and SN to increase understanding of Type II SNe.

OBSERVATIONS & DATA REDUCTION
All data used in this work were taken by the Unistellar Network, comprised of observers worldwide who use Unistellar telescopes -11.4 cm aperture digital, smart telescopes (Marchis et al. 2020). Each telescope employs a CMOS sensor sensitive to blue, green, and red bandpasses via a Bayer filter. Uniform optical properties simplify combination of data from multiple telescopes, making possible results such as those described by Graykowski et al. (2023), Perrocheau et al. (2022), and Peluso et al. (2023).
Unistellar telescopes can record data in two modes, Enhanced Vision (EV) and Science mode, which were utilized to measure the light curve of SN 2023ixf presented in Figure 1. The EV data were taken during prediscovery and postdiscovery serendipitous imaging of M101, while coordinated Science observations commenced ∼29 hr after discovery (Itagaki 2023).
For each observation, raw images were dark-subtracted, if dark frames were taken, and plate-solved. Images that were off-target or had insufficient quality to plate solve were discarded. Calibrated images were aligned and averaged into stacked images with integration time ≈ 60 s. To separate the SN signal from the host galaxy, stacks were highpass filtered using a median boxcar with width equal to 6 aperture radii. Differential aperture photometry was then performed on stacked images to measure fluxes of the SN and 3-5 reference stars with known Gaia magnitudes that were transformed to the Johnson-Cousins V band (Gaia Collaboration et al. 2022). The radius of the circular aperture was minimized to enclose ≥ 90% of the reference stars' flux, which varied from 4 to 12 (3-7 pixels) to accommodate observing conditions.
The SN m V was then calculated as where m V ref is the reference star's apparent V magnitude and F ref and F SN are the measured reference star and SN fluxes, respectively. This was repeated for all reference stars and stacks. Measurements of the SN m V with signal-to-noise ratios < 5 were discarded, and we report the mean of the remaining magnitudes. The standard deviation of magnitudes within a given observation is the reported uncertainty. We consider observations where the SN m V exceeds the standard deviation of the background noise (m V − σ bg ) to be non-detections. We use a Markov Chain Monte Carlo (MCMC) sampling to obtain a best-fit model light curve with an exponential rise and linear decay. We obtain a peak m v = 11.05 ± 0.08 at 2023-05-25 21:37 ± 62 min, corresponding to M V = −18.18 ± 0.09 mag using a distance of 6.71 ± 0.14 Mpc and E(B − V ) = 0.031 mag (Riess et al. 2016). These values strongly agree with those found via meter-class telescopes (e.g., Jacobson-Galan et al. 2023). Our modeling implies an explosion time of 2023-05-18 22:43 ± 15 min, but this is 2.23 hr post earliest detection and not meaningfully constrained because our model is not well-fit to the initial rise (∼1 day, similar to Hosseinzadeh et al. 2023).

CONCLUSION
Here we present a light curve of SN 2023ixf with a 3.3 hr average sampling time over 35 days. Our modeled lightcurve parameters support those gathered by professional telescopes and presented in other works. As such, this study provides crucial data to the community, but also demonstrates the power of a global observing network using telescopes with homogeneous opto-electronics, like Unistellar telescopes.